python代码转c代码 # -*- coding: utf-8 -*- import os.path import dpkt import time import cmath import matplotlib.pyplot as plt import torch from scipy.io import savemat import numpy as np def read_pcap(file_path): list_stamp = [] list_packet = [] # 打开pcap文件 with open(file_path, 'rb') as f: pcap = dpkt.pcap.reader(f) for timestamp, packet in pcap: hex_str = ''.join(f'{c:02x}' for c in packet) # 二进制转为16进制 list_stamp.append(timestamp)


以下是将给定的 Python 代码片段转换为 C 代码的一个初步尝试,但这只是一个简单的转换,实际的完整转换可能会更加复杂,特别是涉及到像 `dpkt` 这样的特定库的功能。 ```c #include <stdio.h> #include <stdlib.h> #include <time.h> typedef struct { double timestamp; char *packet; } PacketInfo; void read_pcap(char *file_path, PacketInfo *packetInfos, int *numPackets) { FILE *f; f = fopen(file_path, "rb"); if (f == NULL) { printf("Error opening file!\n"); return; } int i = 0; double timestamp; char packet[1024]; // 假设最大包大小 while (fread(×tamp, sizeof(double), 1, f) == 1) { fread(packet, sizeof(char), 1024, f); // 读取包数据 packetInfos[i].timestamp = timestamp; packetInfos[i].packet = (char *)malloc(strlen(packet) + 1); strcpy(packetInfos[i].packet, packet); i++; } *numPackets = i; fclose(f); } int main() { char file_path[] = "your_file_path"; PacketInfo *packetInfos = (PacketInfo *)malloc(sizeof(PacketInfo) * 1000); // 假设最大 1000 个包 int numPackets = 0; read_pcap(file_path, packetInfos, &numPackets); // 释放内存 for (int i = 0; i < numPackets; i++) { free(packetInfos[i].packet); } free(packetInfos); return 0; } ``` 这只是一个基础的转换,没有处理像将二进制数据转换为十六进制字符串这样的复杂操作。对于完整和准确的转换,需要更多的工作和对相关功能的 C 语言实现。 [2024-10-29 15:57:32 | AI写代码神器 | 486点数解答]
- python代码转c代码 # -*- coding: utf-8 -*- import os.path import dpkt import time import cmath import matplotlib.pyplot as plt import torch from scipy.io import savemat import numpy as np def read_pcap(file_path): list_stamp = [] list_packet = [] # 打开pcap文件 with open(file_path, 'rb') as f: pcap = dpkt.pcap.reader(f) for timestamp, packet in pcap: hex_str = ''.join(f'{c:02x}' for c in packet) # 二进制转为16进制 list_stamp.append(timestamp)(486点数解答 | 2024-10-29 15:57:32)180
- python代码转c代码 # -*- coding: utf-8 -*- import os.path import dpkt import time import cmath import matplotlib.pyplot as plt import torch from scipy.io import savemat import numpy as np def read_pcap(file_path): list_stamp = [] list_packet = [] # 打开pcap文件 with open(file_path, 'rb') as f: pcap = dpkt.pcap.reader(f) for timestamp, packet in pcap: hex_str = ''.join(f'{c:02x}' for c in packet) # 二进制转为16进制 list_stamp.append(timestamp)(1016点数解答 | 2024-10-29 16:00:17)173
- ```python import numpy as np import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation from mpl_toolkits.mplot3d import Axes3D # 设置图形 fig = plt.figure(figsize=(10, 8)) ax = fig.add_subplot(111, projection='3d') ax.set_facecolor('black') fig.patch.set_facecolor('black') # 爱心参数方程 def heart(t): x = 16 * np.sin(t) 3 y = 13 * np.cos(t) - 5 * np.cos(2*t) - 2 * np.cos(3*t) - np.cos(4*t) return x, y # 生成爱心形状的点 t = np.linspace(0, 2*np.pi, 1000) x, y = heart(t) z = np.(1487点数解答 | 2025-08-07 11:24:56)43
- ```python import numpy as np import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation from mpl_toolkits.mplot3d import Axes3D # 设置图形 fig = plt.figure(figsize=(10, 8)) ax = fig.add_subplot(111, projection='3d') ax.set_facecolor('black') fig.patch.set_facecolor('black') # 爱心参数方程 def heart(t): x = 16 * np.sin(t) 3 y = 13 * np.cos(t) - 5 * np.cos(2*t) - 2 * np.cos(3*t) - np.cos(4*t) return x, y # 生成爱心形状的点 t = np.linspace(0, 2*np.pi, 1000) x, y = heart(t) z = np.(130点数解答 | 2025-08-29 21:24:33)35
- import os import datetime from flask import Flask, request, jsonify import requests from flask_cors import CORS import re import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import numpy as np import base64 from io import BytesIO import pandas as pd import traceback # 添加traceback以获取详细错误信息 plt.rcParams["font.sans-serif"] = ["SimHei"] app = Flask(__name__) CORS(app) FASTGPT_API_URL = 'http://localhost:3000/api/v1/chat/completions' FASTGPT_API_KEY = 'fastgpt-gWzitHpBa8XRr0q(713点数解答 | 2025-06-18 16:00:34)95
- import numpy as np import matplotlib.pyplot as plt from scipy.stats import chi2 import pandas as pd import itertools from statsmodels.stats.outliers_influence import variance_inflation_factor from sklearn.impute import SimpleImputer # 用于简单缺失值填充 import plotly.graph_objects as go from plotly.subplots import make_subplots plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示中文标签 plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号 # 问题背景与意义说明 # 在生产过程中,产品可能会出现多种类型的缺陷,通过对不同缺陷类型的频数分布进行监控, # 可以及时发(925点数解答 | 2025-04-05 17:47:55)117
- 以读、二进制方式打开c盘temp文件夹下abc.txt文件的代码是()[测3] a. f=open(c:/temp/abc.txt,'bt') b. f=open('c://temp//abc.txt','rb') c. f=open('c:\temp\abc.txt','rb') d. f=open('c:/temp/abc.txt','wb') e. f=open('c:\\temp\\abc.txt','rb') f. f=open('c:/temp/abc.txt','rb') g. f=open('c://temp//abc.txt':'rb') h. f=open('c:\\temp\\abc.txt','ab')(15点数解答 | 2024-06-06 13:53:37)269
- 以下代码生成包含广告成本和销售额的模拟数据,用来分析广告投入与销售额之间的关系。请补全以下代码,完成从数据生成到可视化分析的全过程。代码包含8个空缺(空1至空8),请根据上下文和注释提示填入正确的代码。 import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns plt.rcParams['font.sans-serif'] = ['SimHei'] # 生成模拟数据 np.random.seed(123) # 设置随机种子 ad_cost = np.random.uniform(10, 100, 50) # 生成均匀分布数据 sales = 50 + 2.5 * ad_cost + np.random.normal(0, 20, 50) # 生成正态分布噪声 data = pd.______({'Ad_Cost': ad_cost, 'Sales': sales}) # 空1:创建DataFrame print(data) (939点数解答 | 2025-05-26 23:04:07)95
- import javax.swing.*; import java.awt.*; import java.awt.datatransfer.clipboard; import java.awt.datatransfer.stringselection; import java.awt.datatransfer.transferable; import java.awt.event.*; import java.io.*; import java.nio.file.files; import java.nio.file.path; import java.nio.file.paths; import java.time.localdatetime; import java.util.hashmap; import java.util.list; import java.util.map; import java.util.random; public class copy { static private final jtextarea textarea = new jtext(1497点数解答 | 2024-08-25 09:40:33)302
- import win32com.client import os def excel_to_pdf(input_file, output_file): # 确保输入文件存在 if not os.path.exists(input_file): raise FileNotFoundError(f"文件 {input_file} 不存在") # 创建 Excel 应用程序实例 excel = win32com.client.Dispatch("Excel.Application") excel.Visible = False # 不显示 Excel 窗口 try: # 打开 Excel 文件 wb = excel.Workbooks.Open(input_file) # 设置页面布局为 A4 横向 for ws in wb.Worksheets: ws.PageSetup.Orientation = 2 # 2 表示横向 (507点数解答 | 2025-03-10 15:48:12)157
- from kivy.app import app from kivy.uix.button import button from kivy.uix.boxlayout import boxlayout from kivy.uix.filechooser import filechooserlistview from kivy.uix.popup import popup from kivy.uix.label import label from kivy.uix.screenmanager import screenmanager, screen from kivy.core.window import window from kivy.uix.treeview import treeview, treeviewlabel from unitypy import assetsmanager from unitypy.exceptions import unitypyerror import os from pil import image import time class file(262点数解答 | 2024-12-01 17:07:07)196
- import openpyxl import smtplib import imaplib import email import json import os import re from bs4 import BeautifulSoup from fastapi import FastAPI, Form from openpyxl.styles import Alignment from email.mime.multipart import MIMEMultipart from email.mime.base import MIMEBase from email.header import decode_header from email import encoders import pandas as pd app = FastAPI() RECEIVER_EMAILS = { 0: "yundongshijie001@protonmail.com", 1: "xiaobudian001@protonmail.com" } email_address = "(182点数解答 | 2025-04-12 00:49:09)144